Staff Data Site Reliability Engineer

The Hartford

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Hartford, CTChicago, ILColumbus, OHCharlotte, NC
Salary
$127,600–$191,400 / yr
Employment
Full-time
Posted
68 days ago
Freshness
Confirmed live today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $180k
This role $160k
$116k $237k
below market most similar roles pay here above market

This role pays less than 66% of similar roles. Most pay $145,375–$215,000 — the blue band above. At the midpoint, this role pays about $160k versus about $180k for comparable roles.

Based on 240 similar postings.

Employer

About The Hartford

The Hartford is a leading provider of property and casualty insurance, group benefits, and mutual funds, serving businesses and individuals across the United States. Industry: Insurance & Financial Services

The Hartford currently has 70 open roles on FindRole.

Listed pay typically runs $127,600–$191,400 across 29 roles with salary data.

Most-posted roles

View all roles at The Hartford

At a glance

TL;DR · Staff Data Site Reliability Engineer

JOB TITLE: Staff Data Site Reliability Engineer - Hybrid The Staff Data Site Reliability Engineer - Hybrid joins the SRE team to focus on the integrity, quality, and availability of data assets and pipelines. This role concentrates on the data journey layer, ensuring data products are trustworthy for downstream consumers. Key responsibilities include establishing Data Service Level Objectives for freshness and accuracy, implementing advanced data observability tools to detect schema drifts, and automating data validation and reprocessing to eliminate toil. You will collaborate with Data Engineering to embed reliability patterns into pipelines using Informatica, Python/Pyspark, Amazon EMR/Hadoop, Snowflake, and AWS/GCP. The role requires managing data-related incidents, creating automated runbooks, and utilizing AIOps and prompt engineering to monitor and self-heal pipelines within an enterprise data environment.

What you'll do

  • Establish and enforce Data Service Level Objectives (SLOs) for data freshness, completeness, and accuracy.
  • Implement advanced data observability tools to monitor the data journey and detect real-time anomalies.
  • Embed reliability patterns into data pipelines using Informatica, Python/Pyspark, and Amazon EMR.
  • Automate data validation, reprocessing, and backfilling tasks to eliminate manual operational toil.
  • Lead the response and resolution for data-related incidents and conduct blameless post-mortems.
  • Develop and automate data-aware runbooks for common pipeline failures and data recovery scenarios.
  • Implement AIOps and machine learning principles to monitor and self-heal data pipelines.

What we're looking for

  • Bachelor's degree and 5+ years of overall experience in an Infrastructure, Data, or related technology organization.
  • 3+ years of experience in Data Engineering, Data Quality, or a specialized SRE role within an enterprise data environment.
  • Hands-on experience with data warehousing and data lake technologies, including Snowflake, and cloud environments (AWS/GCP).
  • Hands-on experience with ETL pipelines using SQL Server Integration Services (SSIS) and SQL Server Management Studio (SSMS).
  • Hands-on experience in pipeline development and support using Informatica, Python/Pyspark, and distributed compute (EMR/Hadoop).
  • In-depth hands-on experience with data observability concepts and tools for monitoring data in motion and at rest.
  • Experience collaborating with application teams to support .NET framework solutions and ASP.NET web applications (preferred).

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